• Rcpp and C++
• ggplot2
• Using spatial data
• Classification with individual and ensemble trees
• Interactive web graphics with R and googleVis
• Cloud computing
• …

• written by Hadley Wickham
• implementation of the grammar of graphics
• combines the advantages of both base and lattice graphics

• written by Dirk Eddelbuettel and Romain François
• seamless R and C++ integration
  • supports many R data types
  • provides typical R functions and C++ classes

Why use C++ integration in R?

Sometimes, R code is just not fast enough…

• Loops that cannot be vectorized because subsequent iterations depend on previous ones

# Count number of remaining samples (iterations)

nLeft <- 3
for (i in 1:3) {
  cat("Processing sample ", i, ". ", sep = "")

  ## (some sample-related operations)
  
  nLeft <- nLeft - 1
  cat(nLeft, "samples left ...\n")
}

## Processing sample 1. 2 samples left ...
## Processing sample 2. 1 samples left ...
## Processing sample 3. 0 samples left ...

• Recursive function calls

# Fibonacci sequence

fibonacci <- function(x) {
  if (x < 2) {
    return(x)
  } else {
    return(fibonacci(x-1) + fibonacci(x-2))
  }
}

sapply(1:10, fibonacci)

##  [1]  1  1  2  3  5  8 13 21 34 55

An example: the sum function

x <- 1:10000

sum(x)

## [1] 50005000

An example: the sum function

sumR <- function(x) {
  
  total <- 0
  for (i in 1:length(x)) {
    total <- total + x[i]
  }
  
  return(total)
}

sumR(x)

## [1] 50005000

An example: the sum function

library(microbenchmark)

microbenchmark(sum(x), sumR(x), sumC(x), times = 1000L)

## Unit: microseconds
##     expr      min        lq       mean    median       uq       max neval
##   sum(x)    9.637    9.8745   12.61476   11.9305   14.818   236.301  1000
##  sumR(x) 3700.914 3960.5945 4422.09303 4178.9590 4723.615 42668.660  1000
##  sumC(x)   20.961   22.2015   32.14437   32.6745   38.002   185.743  1000

With invited talks by

• Thomas Lumley (R Core Team)
• Adrian Baddeley (spatstat)
• Romain François (Rcpp)
• …

(see http://user2015.math.aau.dk/)

This ioslides presentation was entirely created from R Markdown v2.

For further information, check out
http://blog.rstudio.org/2014/06/18/r-markdown-v2/.